Revert LLMRunFrame for quickstart

Gladia - add missing config parameters

.github/workflows/build.yaml

@@ -21,24 +21,20 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      
+      - name: Set up Python
+        run: uv python install 3.10
+      
+      - name: Install development dependencies
+        run: uv sync --group dev
+      
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
-      - name: Install project and other Python dependencies
-        run: |
-          source .venv/bin/activate
-          pip install --editable .
+        run: uv build
+      
+      - name: Install project in editable mode
+        run: uv pip install --editable .

.github/workflows/coverage.yaml

@@ -18,35 +18,28 @@ jobs:
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
       - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
-        with:
-          python-version: "3.10"
-      - name: Cache virtual environment
-        uses: actions/cache@v3
-        with:
-          # We are hashing dev-requirements.txt and test-requirements.txt which
-          # contain all dependencies needed to run the tests.
-          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
-          path: .venv
+        run: uv python install 3.12
+
       - name: Install system packages
-        id: install_system_packages
         run: |
           sudo apt-get install -y portaudio19-dev
-      - name: Setup virtual environment
+
+      - name: Install dependencies
         run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt -r test-requirements.txt
+          uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
+
       - name: Run tests with coverage
         run: |
-          source .venv/bin/activate
-          coverage run
-          coverage xml
+          uv run coverage run
+          uv run coverage xml
+
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v5
         with:

.github/workflows/format.yaml

@@ -22,25 +22,22 @@ jobs:
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: "3.10"
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install development Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      
+      - name: Set up Python
+        run: uv python install 3.10
+      
+      - name: Install development dependencies
+        run: uv sync --group dev
+      
       - name: Ruff formatter
         id: ruff-format
-        run: |
-          source .venv/bin/activate
-          ruff format --diff
+        run: uv run ruff format --diff
+      
       - name: Ruff linter (all rules)
         id: ruff-check
-        run: |
-          source .venv/bin/activate
-          ruff check
+        run: uv run ruff check

.github/workflows/publish.yaml

@@ -17,23 +17,17 @@ jobs:
         uses: actions/checkout@v4
         with:
           ref: ${{ github.event.inputs.gitref }}
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      - name: Set up Python
+        run: uv python install 3.10
+      - name: Install development dependencies
+        run: uv sync --group dev
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
+        run: uv build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:

.github/workflows/publish_test.yaml

@@ -12,23 +12,16 @@ jobs:
         with:
           fetch-tags: true
           fetch-depth: 100
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      - name: Set up Python
+        run: uv python install 3.10
+      - name: Install development dependencies
+        run: uv sync --group dev
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
+        run: uv build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:
@@ -38,7 +31,7 @@ jobs:
   publish-to-test-pypi:
     name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
-    needs: [ build ]
+    needs: [build]
     environment:
       name: testpypi
       url: https://pypi.org/p/pipecat-ai

.github/workflows/python-compatibility.yaml

@@ -0,0 +1,61 @@
+name: Python Compatibility Test
+
+on:
+  push:
+    branches: [main, develop]
+    paths: ['pyproject.toml']
+  pull_request:
+    branches: [main, develop]
+    paths: ['pyproject.toml']
+
+jobs:
+  test-compatibility:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5']
+
+    name: Python ${{ matrix.python-version }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install system dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y \
+            portaudio19-dev \
+            libcairo2-dev \
+            libgirepository1.0-dev \
+            pkg-config
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+        with:
+          version: 'latest'
+
+      - name: Set up Python ${{ matrix.python-version }}
+        run: |
+          uv python install ${{ matrix.python-version }}
+          uv python pin ${{ matrix.python-version }}
+
+      - name: Test uv sync with all extras (Python < 3.13)
+        if: "!startsWith(matrix.python-version, '3.13.')"
+        run: |
+          uv sync --group dev --all-extras --no-extra krisp
+
+      - name: Test uv sync without PyTorch extras (Python 3.13+)
+        if: startsWith(matrix.python-version, '3.13.')
+        run: |
+          uv sync --group dev --all-extras \
+            --no-extra krisp \
+            --no-extra ultravox \
+            --no-extra local-smart-turn \
+            --no-extra moondream \
+            --no-extra mlx-whisper
+
+      - name: Verify installation
+        run: |
+          uv run python --version
+          uv run python -c "import pipecat; print('✅ Pipecat imports successfully')"

.github/workflows/sync-quickstart.yaml

@@ -23,17 +23,12 @@ jobs:
           token: ${{ secrets.QUICKSTART_SYNC_TOKEN }}
           path: quickstart-repo
 
-      - name: Sync files (excluding READMEs)
+      - name: Sync files (excluding uv.lock and README.md)
         run: |
-          # Copy code files only, skip READMEs
-          cp examples/quickstart/bot.py quickstart-repo/
-          cp examples/quickstart/requirements.txt quickstart-repo/
-          cp examples/quickstart/env.example quickstart-repo/
-
-          # Copy any other files that aren't README.md
+          # Copy all files except uv.lock and README.md
           find examples/quickstart -type f \
             -not -name "README.md" \
-            -not -name "*.md" \
+            -not -name "uv.lock" \
             -exec cp {} quickstart-repo/ \;
 
       - name: Commit and push changes

.github/workflows/tests.yaml

@@ -22,31 +22,23 @@ jobs:
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
       - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
-        with:
-          python-version: "3.10"
-      - name: Cache virtual environment
-        uses: actions/cache@v3
-        with:
-          # We are hashing dev-requirements.txt and test-requirements.txt which
-          # contain all dependencies needed to run the tests.
-          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
-          path: .venv
+        run: uv python install 3.12
+
       - name: Install system packages
-        id: install_system_packages
         run: |
           sudo apt-get install -y portaudio19-dev
-      - name: Setup virtual environment
+
+      - name: Install dependencies
         run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt -r test-requirements.txt
+          uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
+
       - name: Test with pytest
         run: |
-          source .venv/bin/activate
-          pytest
+          uv run pytest

.github/workflows/update-lockfile.yaml

@@ -1,42 +0,0 @@
-name: Update lockfile
-
-on:
-  push:
-    paths:
-      - 'pyproject.toml'
-    branches:
-      - main
-  workflow_dispatch: # Allows manual triggering from GitHub UI
-
-jobs:
-  update-lockfile:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          # This gives the workflow permission to push back to the repo
-          token: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v1
-
-      - name: Update lockfile
-        run: uv lock
-
-      - name: Check for changes
-        id: verify-changed-files
-        run: |
-          if [ -n "$(git status --porcelain)" ]; then
-            echo "changed=true" >> $GITHUB_OUTPUT
-          else
-            echo "changed=false" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Commit lockfile
-        if: steps.verify-changed-files.outputs.changed == 'true'
-        run: |
-          git config --local user.email "action@github.com"  
-          git config --local user.name "GitHub Action"
-          git add uv.lock
-          git commit -m "chore: update uv.lock after dependency changes"
-          git push

.readthedocs.yaml

@@ -9,22 +9,14 @@ build:
     - python3-dev
     - libasound2-dev
   jobs:
-    pre_build:
-      - python -m pip install --upgrade pip
-      - pip install wheel setuptools
-    post_build:
-      - echo "Build completed"
+    post_install:
+      - pip install uv
+      - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
 
 sphinx:
   configuration: docs/api/conf.py
   fail_on_warning: false
 
-python:
-  install:
-    - requirements: docs/api/requirements.txt
-    - method: pip
-      path: .
-
 search:
   ranking:
     api/*: 5

CHANGELOG.md

@@ -7,15 +7,569 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## Added
+
+- Added `pipecat.extensions.ivr` for automated IVR system navigation with
+  configurable goals and conversation handling. Supports DTMF input, verbal
+  responses, and intelligent menu traversal.
+
+  Basic usage:
+
+  ```python
+  from pipecat.extensions.ivr.ivr_navigator import IVRNavigator
+
+  # Create IVR navigator with your goal
+  ivr_navigator = IVRNavigator(
+      llm=llm_service,
+      ivr_prompt="Navigate to billing department to dispute a charge"
+  )
+
+  # Handle different outcomes
+  @ivr_navigator.event_handler("on_conversation_detected")
+  async def on_conversation(processor, conversation_history):
+      # Switch to normal conversation mode
+      pass
+
+  @ivr_navigator.event_handler("on_ivr_status_changed")
+  async def on_ivr_status(processor, status):
+      if status == IVRStatus.COMPLETED:
+          # End pipeline, transfer call, or start bot conversation
+      elif status == IVRStatus.STUCK:
+          # Handle navigation failure
+  ```
+
+- `BaseOutputTransport` now implements `write_dtmf()` by loading DTMF audio and
+  sending it through the transport. This makes sending DTMF generic across all
+  output transports.
+
+- Added new config parameters to `GladiaSTTService`. 
+  - PreProcessingConfig > `audio_enhancer` to enhance audio quality.
+  - CustomVocabularyItem > `pronunciations` and `language` to specify special pronunciations and in which language it will be pronounced.
+
+## Changed
+
+- `pipecat.frames.frames.KeypadEntry` is deprecated and has been moved to
+  `pipecat.audio.dtmf.types.KeypadEntry`.
+
+## Removed
+
+- Remove `StopInterruptionFrame`. This was a legacy frame that was not being
+  used really anywhere and it didn't provide any useful meaning. It was only
+  pushed after `UserStoppedSpeakingFrame`, so developers can just use
+  `UserStoppedSpeakingFrame`.
+
+- `DailyTransport.write_dtmf()` has been removed in favor of the generic
+  `BaseOutputTransport.write_dtmf()`.
+
+- Remove deprecated `DailyTransport.send_dtmf()`.
+
+## Deprecated
+
+- `pipecat.frames.frames.KeypadEntry` is deprecated use
+  `pipecat.audio.dtmf.types.KeypadEntry` instead.
+
+## Fixed
+
+- Fixed an issue where `PipelineTask` was not cleaning up the observers.
+
+## [0.0.82] - 2025-08-28
+
+### Added
+
+- Added a new `LLMRunFrame` to trigger an LLM response:
+
+  ```python
+  await task.queue_frames([LLMRunFrame()])
+  ```
+
+  This replaces `OpenAILLMContextFrame`, which you’d previously typically use
+  like this:
+
+  ```python
+  await task.queue_frames([context_aggregator.user().get_context_frame()])
+  ```
+
+  Use this way of kicking off your conversation when you’ve already initialized
+  your context and are simply instructing the bot when to go:
+
+  ```python
+  context = OpenAILLMContext(messages, tools)
+  context_aggregator = llm.create_context_aggregator(context)
+
+  # ...
+
+  @transport.event_handler("on_client_connected")
+  async def on_client_connected(transport, client):
+      # Kick off the conversation.
+      await task.queue_frames([LLMRunFrame()])
+  ```
+
+  Note that if you want to add new messages when kicking off the conversation,
+  you could use `LLMMessagesAppendFrame` with `run_llm=True` instead:
+
+  ```python
+  @transport.event_handler("on_client_connected")
+  async def on_client_connected(transport, client):
+      # Kick off the conversation.
+      await task.queue_frames([LLMMessagesAppendFrame(new_messages, run_llm=True)])
+  ```
+
+  In the rare case you don’t have a context aggregator in your pipeline, then
+  you may continue using a context frame.
+
+- Added support for switching between audio+text to text-only modes within the
+  same pipeline. This is done by pushing
+  `LLMConfigureOutputFrame(skip_tts=True)` to enter text-only mode, and
+  disabling it to return to audio+text. The LLM will still generate tokens and
+  add them to the context, but they will not be sent to TTS.
+
+- Added `skip_tts` field to `TextFrame`. This lets a text frame bypass TTS while
+  still being included in the LLM context. Useful for cases like structured text
+  that isn’t meant to be spoken but should still contribute to context.
+
+- Added a `cancel_timeout_secs` argument to `PipelineTask` which defines how
+  long the pipeline has to complete cancellation. When `PipelineTask.cancel()`
+  is called, a `CancelFrame` is pushed through the pipeline and must reach the
+  end. If it does not reach the end within the specified time, a warning is
+  shown and the wait is aborted.
+
+- Added a new "universal" (LLM-agnostic) `LLMContext` and accompanying
+  `LLMContextAggregatorPair`, which will eventually replace `OpenAILLMContext`
+  (and the other under-the-hood contexts) and the other context aggregators.
+  The new universal `LLMContext` machinery allows a single context to be shared
+  between different LLMs, enabling runtime LLM switching and scenarios like
+  failover.
+
+  From the developer's point of view, switching to using the new universal
+  context machinery will usually be a matter of going from this:
+
+  ```python
+  context = OpenAILLMContext(messages, tools)
+  context_aggregator = llm.create_context_aggregator(context)
+  ```
+
+  To this:
+
+  ```python
+  context = LLMContext(messages, tools)
+  context_aggregator = LLMContextAggregatorPair(context)
+  ```
+
+  To start, the universal `LLMContext` is supported with the following LLM
+  services:
+
+  - `OpenAILLMService`
+  - `GoogleLLMService`
+
+- Added a new `LLMSwitcher` class to enable runtime LLM switching, built atop a
+  new generic `ServiceSwitcher`.
+
+  Switchers take a switching strategy. The first available strategy is
+  `ServiceSwitcherStrategyManual`.
+
+  To switch LLMs at runtime, the LLMs must be sharing one instance of the new
+  universal `LLMContext` (see above bullet).
+
+  ```python
+  # Instantiate your LLM services
+  llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+  llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
+
+  # Instantiate a switcher
+  # (ServiceSwitcherStrategyManual defaults to OpenAI, as it's first in the list)
+  llm_switcher = LLMSwitcher(
+      llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual
+  )
+
+  # Create your pipeline
+  pipeline = Pipeline(
+    [
+        transport.input(),
+        stt,
+        context_aggregator.user(),
+        llm_switcher,
+        tts,
+        transport.output(),
+        context_aggregator.assistant(),
+    ]
+  )
+  task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
+
+  # ...
+  # Whenever is appropriate, switch LLMs!
+  await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
+  ```
+
+- Added an `LLMService.run_inference()` method to LLM services to enable
+  direct, out-of-band (i.e. out-of-pipeline) inference.
+
 ### Changed
 
+- Updated `daily-python` to 0.19.8.
+
+- `PipelineTask` now waits for `StartFrame` to reach the end of the pipeline
+  before pushing any other frames.
+
+- Updated `CartesiaTTSService` and `CartesiaHttpTTSService` to align with
+  Cartesia's changes for the `speed` parameter. It now takes only an enum of
+  `slow`, `normal`, or `fast`.
+
+- Added support to `AWSBedrockLLMService` for setting authentication
+  credentials through environment variables.
+
+- Updated `SarvamTTSService` to use WebSocket streaming for real-time audio
+  generation with multiple Indian languages, with HTTP support still available
+  via `SarvamHttpTTSService`.
+
+### Fixed
+
+- Fixed an RTVI issue that was causing frames to be pushed before pipeline was
+  properly initialized.
+
+- Fixed some `get_messages_for_logging()` that were returning a JSON string
+  instead of a list.
+
+- Fixed a `DailyTransport` issue that prevented DTMF tones from being sent.
+
+- Fixed a missing import in `SentryMetrics`.
+
+- Fixed `AWSPollyTTSService` to support AWS credential provider chain (IAM
+  roles, IRSA, instance profiles) instead of requiring explicit environment
+  variables.
+
+- Fixed a `CartesiaTTSService` issue that was causing the application to hang
+  after Cartesia's 5 minutes timed out.
+
+- Fixed an issue preventing `SpeechmaticsSTTService` from transcribing audio.
+
+## [0.0.81] - 2025-08-25
+
+### Added
+
+- Added `pipecat.extensions.voicemail`, a module for detecting voicemail vs.
+  live conversation, primarily intended for use in outbound calling scenarios.
+  The voicemail module is optimized for text LLMs only.
+
+- Added new frames to the `idle_timeout_frames` arg: `TranscriptionFrame`,
+  `InterimTranscriptionFrame`, `UserStartedSpeakingFrame`, and
+  `UserStoppedSpeakingFrame`. These additions serve as indicators of user
+  activity in the pipeline idle detection logic.
+
+- Allow passing custom pipeline sink and source processors to a
+  `Pipeline`. Pipeline source and sink processors are used to know and control
+  what's coming in and out of a `Pipeline` processor.
+
+- Added `FrameProcessor.pause_processing_system_frames()` and
+  `FrameProcessor.resume_processing_system_frames()`. These allow to pause and
+  resume the processing of system frame.
+
+- Added new `on_process_frame()` observer method which makes it possible to know
+  when a frame is being processed.
+
+- Added new `FrameProcessor.entry_processor()` method. This allows you to access
+  the first non-compound processor in a pipeline.
+
+- Added `FrameProcessor` properties `processors`, `next` and `previous`.
+
+- `ElevenLabsTTSService` now supports additional runtime changes to the `model`,
+  `language`, and `voice_settings` parameters.
+
+- Added `apply_text_normalization` support to `ElevenLabsTTSService` and
+  `ElevenLabsHttpTTSService`.
+
+- Added `MistralLLMService`, using Mistral's chat completion API.
+
+- Added the ability to retry executing a chat completion after a timeout period
+  for `OpenAILLMService` and its subclasses, `AnthropicLLMService`, and
+  `AWSBedrockLLMService`. The LLM services accept new args:
+  `retry_timeout_secs` and `retry_on_timeout`. This feature is disabled by
+  default.
+
+### Changed
+
+- Updated `daily-python` to 0.19.7.
+
+### Deprecated
+
+- `FrameProcessor.wait_for_task()` is deprecated. Use `await task` or
+  `await asyncio.wait_for(task, timeout)` instead.
+
+### Removed
+
+- Watchdog timers have been removed. They were introduced in 0.0.72 to help
+  diagnose pipeline freezes. Unfortunately, they proved ineffective since they
+  required developers to use Pipecat-specific queues, iterators, and events to
+  correctly reset the timer, which limited their usefulness and added friction.
+
+- Removed unused `FrameProcessor.set_parent()` and
+  `FrameProcessor.get_parent()`.
+
+### Fixed
+
+- Fixed an issue that would cause `PipelineRunner` and `PipelineTask` to not
+  handle external asyncio task cancellation properly.
+
+- Added `SpeechmaticsSTTService` exception handling on connection and sending.
+
+- Replaced `asyncio.wait_for()` for `wait_for2.wait_for()` for Python <
+  3.12. because of issues regarding task cancellation (i.e. cancellation is
+  never propagated).
+  See https://bugs.python.org/issue42130
+
+- Fixed an `AudioBufferProcessor` issues that would cause audio overlap when
+  setting a max buffer size.
+
+- Fixed an issue where `AsyncAITTSService` had very high latency in responding
+  by adding `force=true` when sending the flush command.
+
+### Performance
+
+- Improve `PipelineTask` performance by using direct mode processors and by
+  removing unnecessary tasks.
+
+- Improve `ParallelPipeline` performance by using direct mode, by not
+  creating a task for each frame and every sub-pipeline and also by removing
+  other unnecessary tasks.
+
+- `Pipeline` performance improvements by using direct mode.
+
+### Other
+
+- Added `14w-function-calling-mistal.py` using `MistralLLMService`.
+
+- Added `13j-azure-transcription.py` using `AzureSTTService`.
+
+## [0.0.80] - 2025-08-13
+
+### Added
+
+- Added `GeminiTTSService` which uses Google Gemini to generate TTS output. The
+  Gemini model can be prompted to insert styled speech to control the TTS
+  output.
+
+- Added Exotel support to Pipecat's development runner. You can now connect
+  using the runner with `uv run bot.py -t exotel` and an ngrok connection to
+  HTTP port 7860.
+
+- Added `enable_direct_mode` argument to `FrameProcessor`. The direct mode is
+  for processors which require very little I/O or compute resources, that is
+  processors that can perform their task almost immediately. These type of
+  processors don't need any of the internal tasks and queues usually created by
+  frame processors which means overall application performance might be slightly
+  increased. Use with care.
+
+- Added TTFB metrics for `HeyGenVideoService` and `TavusVideoService`.
+
+- Added `endpoint_id` parameter to `AzureSTTService`. ([Custom EndpointId](https://docs.azure.cn/en-us/ai-services/speech-service/how-to-recognize-speech?pivots=programming-language-python#use-a-custom-endpoint))
+
+### Changed
+
+- `WatchdogPriorityQueue` now requires the items to be inserted to always be
+  tuples and the size of the tuple needs to be specified in the constructor when
+  creating the queue with the `tuple_size` argument.
+
+- Updated Moondream to revision `2025-01-09`.
+
+- Updated `PlayHTHttpTTSService` to no longer use the `pyht` client to remove
+  compatibility issues with other packages. Now you can use the PlayHT HTTP
+  service with other services, like GoogleLLMService.
+
+- Updated `pyproject.toml` to once again pin `numba` to `>=0.61.2` in order to
+  resolve package versioning issues.
+
+- Updated the `STTMuteFilter` to include `VADUserStartedSpeakingFrame` and
+  `VADUserStoppedSpeakingFrame` in the list of frames to filter when the
+  filtering is on.
+
+### Performance
+
+- Improving the latency of the `HeyGenVideoService`.
+
+- Improved some frame processors performance by using the new frame processor
+  direct mode. In direct mode a frame processor will process frames right away
+  avoiding the need for internal queues and tasks. This is useful for some
+  simple processors. For example, in processors that wrap other processors
+  (e.g. `Pipeline`, `ParallelPipeline`), we add one processor before and one
+  after the wrapped processors (internally, you will see them as sources and
+  sinks). These sources and sinks don't do any special processing and they
+  basically forward frames. So, for these simple processors we now enable the
+  new direct mode which avoids creating any internal tasks (and queues) and
+  therefore improves performance.
+
+### Fixed
+
+- Fixed an issue with the `BaseWhisperSTTService` where the language was
+  specified as an enum and not a string.
+
+- Fixed an issue where `SmallWebRTCTransport` ended before TTS finished.
+
+- Fixed an issue in `OpenAIRealtimeBetaLLMService` where specifying a `text`
+  `modalities` didn't result in text being outputted from the model.
+
+- Added SSML reserved character escaping to `AzureBaseTTSService` to properly
+  handle special characters in text sent to Azure TTS. This fixes an issue
+  where characters like `&`, `<`, `>`, `"`, and `'` in LLM-generated text would
+  cause TTS failures.
+
+- Fixed a `WatchdogPriorityQueue` issue that could cause an exception when
+  compating watchdog cancel sentinel items with other items in the queue.
+
+- Fixed an issue that would cause system frames to not be processed with higher
+  priority than other frames. This could cause slower interruption times.
+
+- Fixed an issue where retrying a websocket connection error would result in an
+  error.
+
+### Other
+
+- Add foundation example `19b-openai-realtime-beta-text.py`, showing how to use
+  `OpenAIRealtimeBetaLLMService` to output text to a TTS service.
+
+- Add vision support to release evals so we can run the foundational examples 12
+  series.
+
+- Added foundational example `15a-switch-languages.py` to release evals. It is
+  able to detect if we switched the language properly.
+
+- Updated foundational examples to show how to enclose complex logic
+  (e.g. `ParallelPipeline`) into a single processor so the main pipeline becomes
+  simpler.
+
+- Added `07n-interruptible-gemini.py`, demonstrating how to use
+  `GeminiTTSService`.
+
+## [0.0.79] - 2025-08-07
+
+### Changed
+
+- Changed `pipecat-ai`'s `openai` dependency to `>=1.74.0,<=1.99.1` due to a
+  breaking change in `openai` 1.99.2 ([commit](https://github.com/openai/openai-python/commit/657f551dbe583ffb259d987dafae12c6211fba06))
+
+### Deprecated
+
+- `TTSService.say()` is deprecated, push a `TTSSpeakFrame` instead. Calling
+  functions directly is a discouraged pattern in Pipecat because, for example,
+  it might cause issues with frame ordering.
+
+- `LLMMessagesFrame` is deprecated, in favor of either:
+
+  - `LLMMessagesUpdateFrame` with `run_llm=True`
+  - `OpenAILLMContextFrame` with desired messages in a new context
+
+- `LLMUserResponseAggregator` and `LLMAssistantResponseAggregator` are
+  deprecated, as they depended on the now-deprecated `LLMMessagesFrame`. Use
+  `LLMUserContextAggregator` and `LLMAssistantResponseAggregator` (or
+  LLM-specific subclasses thereof) instead.
+
+## [0.0.78] - 2025-08-07
+
+### Added
+
+- Added `enable_emulated_vad_interruptions` to `LLMUserAggregatorParams`.
+  When user speech is emulated (e.g. when a transcription is received but
+  VAD doesn't detect speech), this parameter controls whether the emulated
+  speech can interrupt the bot. Default is False (emulated speech is ignored
+  while the bot is speaking).
+
+- Added new `handle_sigint` and `handle_sigterm` to `RunnerArguments`. This
+  allows applications to know what settings they should use for the environment
+  they are running on. Also, added `pipeline_idle_timeout_secs` to be able to
+  control the `PipelineTask` idle timeout.
+
+- Added `processor` field to `ErrorFrame` to indicate `FrameProcessor` that
+  generated the error.
+
+- Added new language support for `AWSTranscribeSTTService`. All languages
+  supporting streaming data input are now supported:
+  https://docs.aws.amazon.com/transcribe/latest/dg/supported-languages.html
+
+- Added support for Simli Trinity Avatars. A new `is_trinity_avatar` parameter
+  has been introduced to specify whether the provided `faceId` corresponds to a
+  Trinity avatar, which is required for optimal Trinity avatar performance.
+
+- The development runner how handles custom `body` data for `DailyTransport`.
+  The `body` data is passed to the Pipecat client. You can POST to the `/start`
+  endpoint with a request body of:
+
+  ```
+  {
+      "createDailyRoom": true,
+      "dailyRoomProperties": { "start_video_off": true },
+      "body": { "custom_data": "value" }
+  }
+  ```
+
+  The `body` information is parsed and used in the application. The
+  `dailyRoomProperties` are currently not handled.
+
+- Added detailed latency logging to `UserBotLatencyLogObserver`, capturing
+  average response time between user stop and bot start, as well as minimum and
+  maximum response latency.
+
+- Added Chinese, Japanese, Korean word timestamp support to
+  `CartesiaTTSService`.
+
+- Added `region` parameter to `GladiaSTTService`. Accepted values: eu-west
+  (default), us-west.
+
+### Changed
+
+- System frames are now queued. Before, system frames could be generated from
+  any task and would not guarantee any order which was causing undesired
+  behavior. Also, it was possible to get into some rare recursion issues because
+  of the way system frames were executed (they were executed in-place, meaning
+  calling `push_frame()` would finish after the system frame traversed all the
+  pipeline). This makes system frames more deterministic.
+
+- Changed the default model for both `ElevenLabsTTSService` and
+  `ElevenLabsHttpTTSService` to `eleven_turbo_v2_5`. The rationale for this
+  change is that the Turbo v2.5 model exhibits the most stable voice quality
+  along with very low latency TTFB; latencies are on par with the Flash v2.5
+  model. Also, the Turbo v2.5 model outputs word/timestamp alignment data with
+  correct spacing.
+
+- The development runners `/connect` and `/start` endpoint now both return
+  `dailyRoom` and `dailyToken` in place of the previous `room_url` and `token`.
+
+- Updated the `pipecat.runner.daily` utility to only a take `DAILY_API_URL` and
+  `DAILY_SAMPLE_ROOM_URL` environment variables instead of argparsing `-u` and
+  `-k`, respectively.
+
 - Updated `daily-python` to 0.19.6.
 
 - Changed `TavusVideoService` to send audio or video frames only after the
   transport is ready, preventing warning messages at startup.
 
+- The development runner now strips any provided protocol (e.g. https://) from
+  the proxy address and issues a warning. It also strips trailing `/`.
+
+### Deprecated
+
+- In the `pipecat.runner.daily`, the `configure_with_args()` function is
+  deprecated. Use the `configure()` function instead.
+
+- The development runner's `/connect` endpoint is deprecated and will be
+  removed in a future version. Use the `/start` endpoint in its place. In the
+  meantime, both endpoints work and deliver equivalent functionality.
+
 ### Fixed
 
+- Fixed a `DailyTransport` issue that would result in an unhandled
+  `concurrent.futures.CancelledError` when a future is cancelled.
+
+- Fixed a `RivaSTTService` issue that would result in an unhandled
+  `concurrent.futures.CancelledError` when a future is cancelled when reading
+  from the audio chunks from the incoming audio stream.
+
+- Fixed an issue in the `BaseOutputTransport`, mainly reproducible with
+  `FastAPIWebsocketOutputTransport` when the audio mixer was enabled, where the
+  loop could consume 100% CPU by continuously returning without delay, preventing
+  other asyncio tasks (such as cancellation or shutdown signals) from being
+  processed.
+
+- Fixed an issue where `BotStartedSpeakingFrame` and `BotStoppedSpeakingFrame`
+  were not emitted when using `TavusVideoService` or `HeyGenVideoService`.
+
 - Fixed an issue in `LiveKitTransport` where empty `AudioRawFrame`s were pushed
   down the pipeline. This resulted in warnings by the STT processor.
 - Fixed `PiperTTSService` to send text as a JSON object in the request body,
@@ -32,6 +586,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fixed an issue in `TaskObserver` (a proxy to all observers) that was degrading
   global performance.
 
+### Other
+
+- Added `07aa-interruptible-soniox.py`, `07ab-interruptible-inworld-http.py`,
+  `07ac-interruptible-asyncai.py` and `07ac-interruptible-asyncai-http.py`
+  release evals.
+
 ## [0.0.77] - 2025-07-31
 
 ### Added

CONTRIBUTING.md

@@ -31,6 +31,23 @@ git push origin your-branch-name
 
 Our maintainers will review your PR, and once everything is good, your contributions will be merged!
 
+## Dependency Management
+
+This project uses [uv](https://docs.astral.sh/uv/) for dependency management. The `uv.lock` file is committed to ensure reproducible builds.
+
+### Adding or Updating Dependencies
+
+1. Edit `pyproject.toml` to add/update dependencies
+2. Run `uv lock` to update the lockfile with new dependency resolution
+3. Run `uv sync` to install the updated dependencies locally
+4. Always commit both files together:
+   ```bash
+   git add pyproject.toml uv.lock
+   git commit -m "feat: add new dependency for feature X"
+   ```
+
+**Important:** Never manually edit `uv.lock`. It's auto-generated by `uv lock`.
+
 ## Code Style and Documentation
 
 ### Python Code Style

README.md

@@ -54,12 +54,12 @@ You can connect to Pipecat from any platform using our official SDKs:
 | Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
 | ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                          |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                                                                                                                          |
+| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                                                          |
 | Text-to-Speech      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
 | Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
 | Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
 | Serializers         | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
-| Video               | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| Video               | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
 | Memory              | [mem0](https://docs.pipecat.ai/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
 | Vision & Image      | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
 | Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
@@ -69,80 +69,106 @@ You can connect to Pipecat from any platform using our official SDKs:
 
 ## ⚡ Getting started
 
-You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you’re ready.
+You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you're ready.
 
-```shell
-# Install the module
-pip install pipecat-ai
+1. Install uv
 
-# Set up your environment
-cp dot-env.template .env
-```
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   ```
 
-To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
+   > **Need help?** Refer to the [uv install documentation](https://docs.astral.sh/uv/getting-started/installation/).
 
-```shell
-pip install "pipecat-ai[option,...]"
-```
+2. Install the module
+
+   ```bash
+   # For new projects
+   uv init my-pipecat-app
+   cd my-pipecat-app
+   uv add pipecat-ai
+
+   # Or for existing projects
+   uv add pipecat-ai
+   ```
+
+3. Set up your environment
+
+   ```bash
+   cp env.example .env
+   ```
+
+4. To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
+
+   ```bash
+   uv add "pipecat-ai[option,...]"
+   ```
+
+> **Using pip?** You can still use `pip install pipecat-ai` and `pip install "pipecat-ai[option,...]"` to get set up.
 
 ## 🧪 Code examples
 
 - [Foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational) — small snippets that build on each other, introducing one or two concepts at a time
 - [Example apps](https://github.com/pipecat-ai/pipecat-examples) — complete applications that you can use as starting points for development
 
-## 🛠️ Hacking on the framework itself
+## 🛠️ Contributing to the framework
 
-1. Set up a virtual environment before following these instructions. From the root of the repo:
+### Prerequisites
 
-   ```shell
-   python3 -m venv venv
-   source venv/bin/activate
+**Minimum Python Version:** 3.10
+**Recommended Python Version:** 3.12
+
+### Setup Steps
+
+1. Clone the repository and navigate to it:
+
+   ```bash
+   git clone https://github.com/pipecat-ai/pipecat.git
+   cd pipecat
    ```
 
-2. Install the development dependencies:
+2. Install development and testing dependencies:
 
-   ```shell
-   pip install -r dev-requirements.txt
+   ```bash
+   uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp --no-extra local
    ```
 
-3. Install the git pre-commit hooks (these help ensure your code follows project rules):
+3. Install the git pre-commit hooks:
 
-   ```shell
-   pre-commit install
+   ```bash
+   uv run pre-commit install
    ```
 
-4. Install the `pipecat-ai` package locally in editable mode:
+### Python 3.13+ Compatibility
 
-   ```shell
-   pip install -e .
-   ```
+Some features require PyTorch, which doesn't yet support Python 3.13+. Install using:
 
-   > The `-e` or `--editable` option allows you to modify the code without reinstalling.
+```bash
+uv sync --group dev --all-extras \
+  --no-extra gstreamer \
+  --no-extra krisp \
+  --no-extra local \
+  --no-extra local-smart-turn \
+  --no-extra mlx-whisper \
+  --no-extra moondream \
+  --no-extra ultravox
+```
 
-5. Include optional dependencies as needed. For example:
+> **Tip:** For full compatibility, use Python 3.12: `uv python pin 3.12`
 
-   ```shell
-   pip install -e ".[daily,deepgram,cartesia,openai,silero]"
-   ```
-
-6. (Optional) If you want to use this package from another directory:
-
-   ```shell
-   pip install "path_to_this_repo[option,...]"
-   ```
+> **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
 
 ### Running tests
 
-Install the test dependencies:
+To run all tests, from the root directory:
 
-```shell
-pip install -r test-requirements.txt
+```bash
+uv run pytest
 ```
 
-From the root directory, run:
+Run a specific test suite:
 
-```shell
-pytest
+```bash
+uv run pytest tests/test_name.py
 ```
 
 ### Setting up your editor

dev-requirements.txt

@@ -1,13 +0,0 @@
-build~=1.2.2
-coverage~=7.9.1
-grpcio-tools~=1.67.1
-pip-tools~=7.4.1
-pre-commit~=4.2.0
-pyright~=1.1.402
-pytest~=8.4.1
-pytest-asyncio~=1.0.0
-pytest-aiohttp==1.1.0
-ruff~=0.12.1
-setuptools~=78.1.1
-setuptools_scm~=8.3.1
-python-dotenv~=1.1.1

docs/README.md

@@ -1,10 +0,0 @@
-# Pipecat Docs
-
-## [Architecture Overview](architecture.md)
-
-Learn about the thinking behind the framework's design.
-
-## [A Frame's Progress](frame-progress.md)
-
-See how a Frame is processed through a Transport, a Pipeline, and a series of Frame Processors.
-

docs/api/build-docs.sh

@@ -1,17 +1,27 @@
 #!/bin/bash
 
-# Check if sphinx-build is installed
-if ! command -v sphinx-build &> /dev/null; then
-    echo "Error: sphinx-build is not installed or not in PATH" >&2
-    echo "Please install Sphinx using: pip install -r requirements.txt" >&2
+# Build docs using uv
+echo "Installing dependencies with uv..."
+uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
+
+# Check if sphinx-build is available
+if ! uv run sphinx-build --version &> /dev/null; then
+    echo "Error: sphinx-build is not available" >&2
     exit 1
 fi
 
 # Clean previous build
 rm -rf _build
 
+echo "Building documentation..."
 # Build docs matching ReadTheDocs configuration
-sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
+uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
 
-# Open docs (MacOS)
-open _build/html/index.html
+if [ $? -eq 0 ]; then
+    echo "Documentation built successfully!"
+    # Open docs (MacOS)
+    open _build/html/index.html
+else
+    echo "Documentation build failed!" >&2
+    exit 1
+fi

docs/api/conf.py

@@ -1,4 +1,5 @@
 import logging
+import os
 import sys
 from datetime import datetime
 from pathlib import Path
@@ -28,6 +29,7 @@ extensions = [
 
 suppress_warnings = [
     "autodoc.mocked_object",
+    "toc.not_included",
 ]
 
 # Napoleon settings
@@ -45,85 +47,40 @@ autodoc_default_options = {
 
 # Mock imports for optional dependencies
 autodoc_mock_imports = [
-    "riva",
-    "livekit",
-    "pyht",  # Base PlayHT package
-    "pyht.async_client",  # PlayHT specific imports
-    "pyht.client",
-    "pyht.protos",
-    "pyht.protos.api_pb2",
-    "pipecat_ai_playht",  # PlayHT wrapper
-    "aiortc",
-    "aiortc.mediastreams",
-    "cv2",
-    "av",
-    "pyneuphonic",
-    "mem0",
-    "mlx_whisper",
-    "anthropic",
-    "assemblyai",
-    "boto3",
-    "azure",
-    "cartesia",
-    "deepgram",
-    "elevenlabs",
-    "fal",
-    "gladia",
-    "google",
-    "krisp",
-    "langchain",
-    "lmnt",
-    "noisereduce",
-    "openpipe",
-    "simli",
-    "soundfile",
-    "soniox",
+    # Krisp - has build issues on some platforms
     "pipecat_ai_krisp",
-    "pyaudio",
+    "krisp",
+    # System-specific GUI libraries
     "_tkinter",
     "tkinter",
-    "daily",
-    "daily_python",
-    # Moondream dependencies
-    "torch",
-    "transformers",
-    "intel_extension_for_pytorch",
-    # Ultravox dependencies
-    "huggingface_hub",
+    # Platform-specific audio libraries (if needed)
+    "gi",
+    "gi.require_version",
+    "gi.repository",
+    # OpenCV - sometimes has import issues during docs build
+    "cv2",
+    # Heavy ML packages excluded from ReadTheDocs
+    # ultravox dependencies
     "vllm",
     "vllm.engine.arg_utils",
+    # local-smart-turn dependencies
+    "coremltools",
+    "coremltools.models",
+    "coremltools.models.MLModel",
+    "torch",
+    "torch.nn",
+    "torch.nn.functional",
+    "torchaudio",
+    # moondream dependencies
+    "transformers",
     "transformers.AutoTokenizer",
-    # Langchain dependencies
-    "langchain_core",
-    "langchain_core.messages",
-    "langchain_core.runnables",
-    "langchain_core.messages.AIMessageChunk",
-    "langchain_core.runnables.Runnable",
-    # LiveKit dependencies
-    "livekit",
-    "livekit.rtc",
-    "livekit_api",
-    "livekit_protocol",
-    "tenacity",
-    "tenacity.retry",
-    "tenacity.stop_after_attempt",
-    "tenacity.wait_exponential",
-    "rtc",
-    "rtc.Room",
-    "rtc.RoomOptions",
-    "rtc.AudioSource",
-    "rtc.LocalAudioTrack",
-    "rtc.TrackPublishOptions",
-    "rtc.TrackSource",
-    "rtc.AudioStream",
-    "rtc.AudioFrameEvent",
-    "rtc.AudioFrame",
-    "rtc.Track",
-    "rtc.TrackKind",
-    "rtc.RemoteParticipant",
-    "rtc.RemoteTrackPublication",
-    "rtc.DataPacket",
-    # Riva dependencies
+    "transformers.AutoFeatureExtractor",
+    "AutoFeatureExtractor",
+    "timm",
+    "einops",
+    "intel_extension_for_pytorch",
+    "huggingface_hub",
+    # riva dependencies
     "riva",
     "riva.client",
     "riva.client.Auth",
@@ -133,57 +90,14 @@ autodoc_mock_imports = [
     "riva.client.AudioEncoding",
     "riva.client.proto.riva_tts_pb2",
     "riva.client.SpeechSynthesisService",
-    # Local CoreML Smart Turn dependencies
-    "coremltools",
-    "coremltools.models",
-    "coremltools.models.MLModel",
-    "torch",
-    "torch.nn",
-    "torch.nn.functional",
-    "transformers",
-    "transformers.AutoFeatureExtractor",
-    # Also add specific classes that are imported
-    "AutoFeatureExtractor",
-    # Sentry dependencies
-    "sentry_sdk",
-    # AWS Nova Sonic dependencies
-    "aws_sdk_bedrock_runtime",
-    "aws_sdk_bedrock_runtime.client",
-    "aws_sdk_bedrock_runtime.config",
-    "aws_sdk_bedrock_runtime.models",
-    "smithy_aws_core",
-    "smithy_aws_core.credentials_resolvers",
-    "smithy_aws_core.credentials_resolvers.static",
-    "smithy_aws_core.identity",
-    "smithy_core",
-    "smithy_core.aio",
-    "smithy_core.aio.eventstream",
-    # MCP dependencies (you may already have these)
-    "mcp",
-    "mcp.client",
-    "mcp.client.session_group",
-    "mcp.client.sse",
-    "mcp.client.stdio",
-    "mcp.ClientSession",
-    "mcp.StdioServerParameters",
-    # gstreamer
-    "gi",
-    "gi.require_version",
-    "gi.repository",
-    # Protobuf mocks
-    "pipecat.frames.protobufs.frames_pb2",
-    "pipecat.serializers.protobuf",
-    "google.protobuf",
-    "google.protobuf.descriptor",
-    "google.protobuf.descriptor_pool",
-    "google.protobuf.runtime_version",
-    "google.protobuf.symbol_database",
-    "google.protobuf.internal.builder",
+    # MLX dependencies (Apple Silicon specific)
+    "mlx",
+    "mlx_whisper",  # Note: might need underscore format too
 ]
 
 # HTML output settings
 html_theme = "sphinx_rtd_theme"
-html_static_path = ["_static"]
+html_static_path = ["_static"] if os.path.exists("_static") else []
 autodoc_typehints = "signature"  # Show type hints in the signature only, not in the docstring
 html_show_sphinx = False
 

docs/api/index.rst

@@ -14,13 +14,14 @@ Quick Links
 * `Join our Community <https://discord.gg/pipecat>`_
 
 .. toctree::
-   :maxdepth: 3
+   :maxdepth: 2
    :caption: API Reference
    :hidden:
 
    Adapters <api/pipecat.adapters>
    Audio <api/pipecat.audio>
    Clocks <api/pipecat.clocks>
+   Extensions <api/pipecat.extensions>
    Frames <api/pipecat.frames>
    Metrics <api/pipecat.metrics>
    Observers <api/pipecat.observers>

docs/api/requirements.txt

@@ -1,59 +0,0 @@
-# Sphinx dependencies
-sphinx>=8.1.3
-sphinx-rtd-theme
-sphinx-markdown-builder
-sphinx-autodoc-typehints
-toml
-
-# Install all extras individually to ensure they're properly resolved
-pipecat-ai[anthropic]
-pipecat-ai[assemblyai]
-pipecat-ai[asyncai]
-pipecat-ai[aws]
-pipecat-ai[azure]
-pipecat-ai[cartesia]
-pipecat-ai[cerebras]
-pipecat-ai[deepseek]
-pipecat-ai[daily]
-pipecat-ai[deepgram]
-pipecat-ai[elevenlabs]
-pipecat-ai[fal]
-pipecat-ai[fireworks]
-pipecat-ai[fish]
-pipecat-ai[gladia]
-pipecat-ai[google]
-pipecat-ai[grok]
-pipecat-ai[groq]
-pipecat-ai[inworld]
-# pipecat-ai[krisp] # Mocked
-pipecat-ai[koala]
-# pipecat-ai[langchain] # Mocked
-# pipecat-ai[livekit] # Mocked
-pipecat-ai[lmnt]
-pipecat-ai[local]
-# pipecat-ai[local-smart-turn] # Mocked
-# pipecat-ai[mem0] # Mocked
-# pipecat-ai[mlx-whisper] # Mocked
-# pipecat-ai[moondream] # Mocked
-pipecat-ai[nim]
-# pipecat-ai[neuphonic] # Mocked
-pipecat-ai[noisereduce]
-pipecat-ai[openai]
-# pipecat-ai[openpipe]
-# pipecat-ai[playht] # Mocked due to grpcio conflict with riva
-pipecat-ai[qwen]
-pipecat-ai[remote-smart-turn]
-# pipecat-ai[riva] # Mocked
-pipecat-ai[runner]
-pipecat-ai[sambanova]
-pipecat-ai[silero]
-pipecat-ai[simli]
-pipecat-ai[soundfile]
-pipecat-ai[soniox]
-pipecat-ai[speechmatics]
-pipecat-ai[tavus]
-pipecat-ai[together]
-# pipecat-ai[ultravox] # Mocked
-# pipecat-ai[webrtc] # Mocked
-pipecat-ai[websocket]
-pipecat-ai[whisper]

docs/architecture.md

@@ -1,17 +0,0 @@
-# Pipecat architecture guide
-
-## Frames
-
-Frames can represent discrete chunks of data, for instance a chunk of text, a chunk of audio, or an image. They can also be used to as control flow, for instance a frame that indicates that there is no more data available, or that a user started or stopped talking. They can also represent more complex data structures, such as a message array used for an LLM completion.
-
-## FrameProcessors
-
-Frame processors operate on frames. Every frame processor implements a `process_frame` method that consumes one frame and produces zero or more frames. Frame processors can do simple transforms, such as concatenating text fragments into sentences, or they can treat frames as input for an AI Service, and emit chat completions based on message arrays or transform text into audio or images.
-
-## Pipelines
-
-Pipelines are lists of frame processors linked together. Frame processors can push frames upstream or downstream to their peers. A very simple pipeline might chain an LLM frame processor to a text-to-speech frame processor, with a transport as an output.
-
-## Transports
-
-Transports provide input and output frame processors to receive or send frames respectively. For example, the `DailyTransport` does this with a WebRTC session joined to a Daily.co room.

docs/frame-progress.md

@@ -1,46 +0,0 @@
-# A Frame's Progress
-
-1. A user says “Hello, LLM” and the cloud transcription service delivers a transcription to the Transport.
-![A transcript frame arrives](images/frame-progress-01.png)
-
-2. The Transport places a Transcription frame in the Pipeline’s source queue.
-![Frame in source queue](images/frame-progress-02.png)
-
-3. The Pipeline passes the Transcription frame to the first Frame Processor in its list, the LLM User Message Aggregator.
-![To UMA](images/frame-progress-03.png)
-
-4. The LLM User Message Aggregator updates the LLM Context with a `{“user”: “Hello LLM”}` message.
-![Update context](images/frame-progress-04.png)
-
-5. The LLM User Message Aggregator yields an LLM Message Frame, containing the updated LLM Context. The Pipeline passes this frame to the LLM Frame Processor.
-![Update context](images/frame-progress-05.png)
-
-6. The LLM Frame Processor creates a streaming chat completion based on the LLM context and yields the first chunk of a response, Text Frame with the value “Hi, “. The Pipeline passes this frame to the TTS Frame Processor. The TTS Frame Processor aggregates this response but doesn’t yield anything, yet, because it’s waiting for a full sentence.
-![LLM yields Text](images/frame-progress-06.png)
-
-7. The LLM Frame Processor yields another Text Frame with the value “there.”. The Pipeline passes this frame to the TTS Frame Processor.
-![LLM yields more Text](images/frame-progress-07.png)
-
-8. The TTS Frame Processor now has a full sentence, so it starts streaming audio based on “Hi, there.” It yields the first chunk of streaming audio as an Audio frame, which the Pipeline passes to the LLM Assistant Message Aggregator.
-![TTS yields Audio](images/frame-progress-08.png)
-
-9. The LLM Assistant Message Aggregator doesn’t do anything with Audio frames, so it immediately yields the frame, unchanged. This is the convention for all Frame Processors: frames that the processor doesn’t process should be immediately yielded.
-![pass-through](images/frame-progress-09.png)
-
-10. The Pipeline places the first Audio frame in its sink queue, which is being watched by the Transport. Since the frame is now in a queue, the Pipeline can continue processing other frames. Note that the source and sink queues form a sort of “boundary of concurrent processing” between a Pipeline and the outside world. In a Pipeline, Frames are processed sequentially; once a Frame is on a queue it can be processed in parallel with the frames being processed by the Pipeline. TODO: link to a more in-depth section about this.
-![sink queue](images/frame-progress-10.png)
-
-11. The TTS Frame Processor yields another Audio frame as the Transport transmits the first Audio frame.
-![parallel audio](images/frame-progress-11.png)
-
-12. As before, the LLM Assistant Message Aggregator immediately yields the Audio frame and the Pipeline places the Audio frame in the sink queue.
-![sink queue 2](images/frame-progress-12.png)
-
-13. The TTS Frame Processor has no more frames to yield. The LLM Frame Processor emits an LLM Response End Frame, which the Pipeline passes to the TTS Frame Processor.
-![response end](images/frame-progress-13.png)
-
-14. The TTS Frame Processor immediately yields the LLM Response End Frame, so the Pipeline passes it along to the LLM Assistant Message Aggregator. The LLM Assistant Message Aggregator updates the LLM Context with the full response from the LLM. TODO TODO: I realized I forgot that the TSS Frame Processor also yields the Text frames that the LLM emitted so that the LLM Assistant Message Aggregator could accumulate them, arrggh.
-![response end](images/frame-progress-14.png)
-
-15. The system is quiet, and waiting for the next message from the Transport.
-![response end](images/frame-progress-15.png)

docs/frame.md

@@ -1,110 +0,0 @@
-# Understanding Different Frame Types in the Pipecat System
-
-In the Pipecat system, frames are used to represent different types of data and control signals that flow through the pipeline. Understanding these frame types is crucial for working with the system effectively. This tutorial will cover the main categories of frames and their specific uses.
-
-## 1. Base Frame Classes
-
-### Frame
-The `Frame` class is the base class for all frames. It includes:
-- `id`: A unique identifier
-- `name`: A descriptive name
-- `pts`: Presentation timestamp (optional)
-
-### DataFrame
-`DataFrame` is a subclass of `Frame` and serves as a base for most data-carrying frames.
-
-## 2. Audio Frames
-
-### AudioRawFrame
-Represents a chunk of audio with properties:
-- `audio`: Raw audio data
-- `sample_rate`: Audio sample rate
-- `num_channels`: Number of audio channels
-
-Subclasses include:
-- `InputAudioRawFrame`: For audio from input sources
-- `OutputAudioRawFrame`: For audio to be played by output devices
-- `TTSAudioRawFrame`: For audio generated by Text-to-Speech services
-
-## 3. Image Frames
-
-### ImageRawFrame
-Represents an image with properties:
-- `image`: Raw image data
-- `size`: Image dimensions
-- `format`: Image format (e.g., JPEG, PNG)
-
-Subclasses include:
-- `InputImageRawFrame`: For images from input sources
-- `OutputImageRawFrame`: For images to be displayed
-- `UserImageRawFrame`: For images associated with a specific user
-- `VisionImageRawFrame`: For images with associated text for description
-- `URLImageRawFrame`: For images with an associated URL
-
-### SpriteFrame
-Represents an animated sprite, containing a list of `ImageRawFrame` objects.
-
-## 4. Text and Transcription Frames
-
-### TextFrame
-Represents a chunk of text, used for various purposes in the pipeline.
-
-### TranscriptionFrame
-A specialized `TextFrame` for speech transcriptions, including:
-- `user_id`: ID of the speaking user
-- `timestamp`: When the transcription was generated
-- `language`: Detected language of the speech
-
-### InterimTranscriptionFrame
-Similar to `TranscriptionFrame`, but for interim (not final) transcriptions.
-
-## 5. LLM (Language Model) Frames
-
-### LLMMessagesFrame
-Contains a list of messages for an LLM service to process.
-
-### LLMMessagesAppendFrame and LLMMessagesUpdateFrame
-Used to modify the current context of LLM messages.
-
-### LLMSetToolsFrame
-Specifies tools (functions) available for the LLM to use.
-
-### LLMEnablePromptCachingFrame
-Controls prompt caching in certain LLMs.
-
-## 6. System and Control Frames
-
-### SystemFrame
-Base class for system-level frames.
-
-Important system frames include:
-- `StartFrame`: Initiates a pipeline
-- `CancelFrame`: Stops a pipeline immediately
-- `ErrorFrame`: Notifies of errors (with `FatalErrorFrame` for unrecoverable errors)
-- `EndTaskFrame` and `CancelTaskFrame`: Control pipeline tasks
-- `StartInterruptionFrame` and `StopInterruptionFrame`: Indicate user speech for interruptions
-
-### ControlFrame
-Base class for control-flow frames.
-
-Notable control frames:
-- `EndFrame`: Signals the end of a pipeline
-- `LLMFullResponseStartFrame` and `LLMFullResponseEndFrame`: Bracket LLM responses
-- `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame`: Indicate user speech activity
-- `BotStartedSpeakingFrame` and `BotStoppedSpeakingFrame`: Indicate bot speech activity
-- `TTSStartedFrame` and `TTSStoppedFrame`: Bracket Text-to-Speech responses
-
-## 7. Special Purpose Frames
-
-### MetricsFrame
-Contains performance metrics data.
-
-### FunctionCallInProgressFrame and FunctionCallResultFrame
-Used for handling LLM function (tool) calls.
-
-### ServiceUpdateSettingsFrame
-Base class for updating service settings, with specific subclasses for LLM, TTS, and STT services.
-
-## Conclusion
-
-Understanding these frame types is essential for working with the Pipecat system. Each frame type serves a specific purpose in the pipeline, whether it's carrying data (like audio or images), controlling the flow of the pipeline, or managing system-level operations. By using the appropriate frame types, you can effectively process and transmit various kinds of information through your pipeline.

env.example

@@ -29,6 +29,9 @@ CARTESIA_API_KEY=...
 DAILY_API_KEY=...
 DAILY_SAMPLE_ROOM_URL=https://...
 
+# Deepgram
+DEEPGRAM_API_KEY=...
+
 # ElevenLabs
 ELEVENLABS_API_KEY=...
 ELEVENLABS_VOICE_ID=...
@@ -44,11 +47,21 @@ FIREWORKS_API_KEY=...
 
 # Gladia
 GLADIA_API_KEY=...
+GLADIA_REGION=...
+
+# Google
+GOOGLE_API_KEY=...
+GOOGLE_CLOUD_PROJECT_ID=...
+GOOGLE_TEST_CREDENTIALS=...
+GOOGLE_VERTEX_TEST_CREDENTIALS=...
 
 # LMNT
 LMNT_API_KEY=...
 LMNT_VOICE_ID=...
 
+# Perplexity
+PERPLEXITY_API_KEY=...
+
 # PlayHT
 PLAY_HT_USER_ID=...
 PLAY_HT_API_KEY=...
@@ -122,7 +135,6 @@ SONIOX_API_KEY=
 # Speechmatics
 SPEECHMATICS_API_KEY=...
 
-
 # SambaNova
 SAMBANOVA_API_KEY=...
 
@@ -130,4 +142,4 @@ SAMBANOVA_API_KEY=...
 SENTRY_DSN=...
 
 # Heygen
-HEYGEN_API_KEY=...
+HEYGEN_API_KEY=...

examples/foundational/01-say-one-thing-piper.py

@@ -34,7 +34,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -43,14 +43,17 @@ async def run_bot(transport: BaseTransport):
             base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000
         )
 
-        task = PipelineTask(Pipeline([tts, transport.output()]))
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
 
         # Register an event handler so we can play the audio when the client joins
         @transport.event_handler("on_client_connected")
         async def on_client_connected(transport, client):
             await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -58,7 +61,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/01-say-one-thing-rime.py

@@ -33,7 +33,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -44,14 +44,17 @@ async def run_bot(transport: BaseTransport):
             aiohttp_session=session,
         )
 
-        task = PipelineTask(Pipeline([tts, transport.output()]))
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
 
         # Register an event handler so we can play the audio when the client joins
         @transport.event_handler("on_client_connected")
         async def on_client_connected(transport, client):
             await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -59,7 +62,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/01-say-one-thing.py

@@ -33,7 +33,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = CartesiaTTSService(
@@ -41,14 +41,17 @@ async def run_bot(transport: BaseTransport):
         voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
     )
 
-    task = PipelineTask(Pipeline([tts, transport.output()]))
+    task = PipelineTask(
+        Pipeline([tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -56,7 +59,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/01c-fastpitch.py

@@ -33,19 +33,22 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
 
-    task = PipelineTask(Pipeline([tts, transport.output()]))
+    task = PipelineTask(
+        Pipeline([tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -53,7 +56,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/02-llm-say-one-thing.py

@@ -9,10 +9,14 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
+from pipecat.frames.frames import EndFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -34,7 +38,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = CartesiaTTSService(
@@ -51,14 +55,17 @@ async def run_bot(transport: BaseTransport):
         }
     ]
 
-    task = PipelineTask(Pipeline([llm, tts, transport.output()]))
+    task = PipelineTask(
+        Pipeline([llm, tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
+        await task.queue_frames([OpenAILLMContextFrame(OpenAILLMContext(messages)), EndFrame()])
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -66,7 +73,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/03-still-frame.py

@@ -40,7 +40,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -51,7 +51,10 @@ async def run_bot(transport: BaseTransport):
             key=os.getenv("FAL_KEY"),
         )
 
-        task = PipelineTask(Pipeline([imagegen, transport.output()]))
+        task = PipelineTask(
+            Pipeline([imagegen, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
 
         # Register an event handler so we can play the audio when the client joins
         @transport.event_handler("on_client_connected")
@@ -63,7 +66,7 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -71,7 +74,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/03b-still-frame-imagen.py

@@ -39,7 +39,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     imagegen = GoogleImageGenService(
@@ -52,6 +52,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     # Register an event handler so we can play the audio when the client joins
@@ -66,7 +67,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -74,7 +75,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/04-transports-small-webrtc.py

@@ -18,6 +18,7 @@ from loguru import logger
 from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -103,7 +104,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

examples/foundational/04a-transports-daily.py

@@ -13,6 +13,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -86,7 +87,7 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):

examples/foundational/04b-transports-livekit.py

@@ -9,7 +9,6 @@ import json
 import os
 import sys
 
-from deepgram import LiveOptions
 from dotenv import load_dotenv
 from loguru import logger
 
@@ -51,12 +50,7 @@ async def main():
         ),
     )
 
-    stt = DeepgramSTTService(
-        api_key=os.getenv("DEEPGRAM_API_KEY"),
-        live_options=LiveOptions(
-            vad_events=True,
-        ),
-    )
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
     llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
@@ -78,20 +72,20 @@ async def main():
     context = OpenAILLMContext(messages)
     context_aggregator = llm.create_context_aggregator(context)
 
-    runner = PipelineRunner()
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
 
     task = PipelineTask(
-        Pipeline(
-            [
-                transport.input(),
-                stt,
-                context_aggregator.user(),
-                llm,
-                tts,
-                transport.output(),
-                context_aggregator.assistant(),
-            ],
-        ),
+        pipeline,
         params=PipelineParams(
             enable_metrics=True,
             enable_usage_metrics=True,
@@ -132,6 +126,8 @@ async def main():
             ],
         )
 
+    runner = PipelineRunner()
+
     await runner.run(task)
 
 

examples/foundational/05-sync-speech-and-image.py

@@ -15,13 +15,16 @@ from pipecat.frames.frames import (
     DataFrame,
     Frame,
     LLMFullResponseStartFrame,
-    LLMMessagesFrame,
     TextFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
@@ -83,7 +86,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     """Run the Calendar Month Narration bot using WebRTC transport.
 
     Args:
@@ -153,9 +156,12 @@ async def run_bot(transport: BaseTransport):
                 }
             ]
             frames.append(MonthFrame(month=month))
-            frames.append(LLMMessagesFrame(messages))
+            frames.append(OpenAILLMContextFrame(OpenAILLMContext(messages)))
 
-        task = PipelineTask(pipeline)
+        task = PipelineTask(
+            pipeline,
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
 
         # Set up transport event handlers
         @transport.event_handler("on_client_connected")
@@ -170,14 +176,14 @@ async def run_bot(transport: BaseTransport):
             await task.cancel()
 
         # Run the pipeline
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
         await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/05a-local-sync-speech-and-image.py

@@ -15,7 +15,6 @@ from loguru import logger
 
 from pipecat.frames.frames import (
     Frame,
-    LLMMessagesFrame,
     OutputAudioRawFrame,
     TextFrame,
     TTSAudioRawFrame,
@@ -25,6 +24,10 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia.tts import CartesiaHttpTTSService
@@ -137,7 +140,7 @@ async def main():
             )
 
             task = PipelineTask(pipeline)
-            await task.queue_frame(LLMMessagesFrame(messages))
+            await task.queue_frame(OpenAILLMContextFrame(OpenAILLMContext(messages)))
             await task.stop_when_done()
 
             await runner.run(task)

examples/foundational/06-listen-and-respond.py

@@ -10,7 +10,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, MetricsFrame
+from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame
 from pipecat.metrics.metrics import (
     LLMUsageMetricsData,
     ProcessingMetricsData,
@@ -76,7 +76,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -119,6 +119,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -126,21 +127,21 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
     await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/06a-image-sync.py

@@ -15,6 +15,7 @@ from pipecat.frames.frames import (
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
     Frame,
+    LLMRunFrame,
     OutputImageRawFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
@@ -91,7 +92,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -137,27 +138,28 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
     await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07-interruptible-cartesia-http.py

@@ -10,6 +10,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,6 +89,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -95,14 +97,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -110,7 +112,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07-interruptible.py

@@ -10,6 +10,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -47,7 +48,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -87,6 +88,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -94,14 +96,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -109,7 +111,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07a-interruptible-speechmatics-vad.py

@@ -9,6 +9,7 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     """Speechmatics STT Service Example
 
     This example demonstrates using Speechmatics Speech-to-Text service with speaker diarization and intelligent speaker management. Key features:
@@ -146,6 +147,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -153,14 +155,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Say a short hello to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -168,7 +170,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07a-interruptible-speechmatics.py

@@ -10,6 +10,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -52,7 +53,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     """Run example using Speechmatics STT.
 
     This example will use diarization within our STT service and output the words spoken by
@@ -129,6 +130,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -136,14 +138,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Say a short hello to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -151,7 +153,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07aa-interruptible-soniox.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -45,7 +46,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = SonioxSTTService(
@@ -86,6 +87,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -93,14 +95,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -108,7 +110,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07ab-interruptible-inworld-http.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -101,6 +102,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -108,14 +110,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -123,7 +125,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07ac-interruptible-asyncai-http.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -50,7 +51,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -93,6 +94,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -100,14 +102,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -115,7 +117,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07ac-interruptible-asyncai.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -89,6 +90,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -96,14 +98,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -111,7 +113,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07b-interruptible-langchain.py

@@ -16,15 +16,20 @@ from langchain_openai import ChatOpenAI
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.frames.frames import LLMMessagesUpdateFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
 )
 from pipecat.processors.frameworks.langchain import LangchainProcessor
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
@@ -65,7 +70,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -95,8 +100,9 @@ async def run_bot(transport: BaseTransport):
     )
     lc = LangchainProcessor(history_chain)
 
-    tma_in = LLMUserResponseAggregator()
-    tma_out = LLMAssistantResponseAggregator()
+    context = OpenAILLMContext()
+    tma_in = LLMUserContextAggregator(context=context)
+    tma_out = LLMAssistantContextAggregator(context=context)
 
     pipeline = Pipeline(
         [
@@ -116,24 +122,25 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        # the `LLMMessagesFrame` will be picked up by the LangchainProcessor using
+        # An `OpenAILLMContextFrame` will be picked up by the LangchainProcessor using
         # only the content of the last message to inject it in the prompt defined
         # above. So no role is required here.
         messages = [({"content": "Please briefly introduce yourself to the user."})]
-        await task.queue_frames([LLMMessagesFrame(messages)])
+        await task.queue_frames([LLMMessagesUpdateFrame(messages, run_llm=True)])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -141,7 +148,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07c-interruptible-deepgram-vad.py

@@ -12,8 +12,8 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.frames.frames import (
-    BotInterruptionFrame,
-    StopInterruptionFrame,
+    LLMRunFrame,
+    StartInterruptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
@@ -52,7 +52,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(
@@ -92,29 +92,30 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @stt.event_handler("on_speech_started")
     async def on_speech_started(stt, *args, **kwargs):
-        await task.queue_frames([BotInterruptionFrame(), UserStartedSpeakingFrame()])
+        await task.queue_frames([StartInterruptionFrame(), UserStartedSpeakingFrame()])
 
     @stt.event_handler("on_utterance_end")
     async def on_utterance_end(stt, *args, **kwargs):
-        await task.queue_frames([StopInterruptionFrame(), UserStoppedSpeakingFrame()])
+        await task.queue_frames([UserStoppedSpeakingFrame()])
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -122,7 +123,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07c-interruptible-deepgram.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -86,6 +87,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -93,14 +95,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -108,7 +110,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07d-interruptible-elevenlabs-http.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -50,7 +51,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -93,6 +94,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -100,14 +102,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -115,7 +117,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07d-interruptible-elevenlabs.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -89,6 +90,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -96,14 +98,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -111,7 +113,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07e-interruptible-playht-http.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -89,6 +90,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -96,14 +98,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -111,7 +113,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07e-interruptible-playht.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -91,6 +92,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -98,14 +100,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -113,7 +115,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07f-interruptible-azure.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = AzureSTTService(
@@ -95,6 +96,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -102,14 +104,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -117,7 +119,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07g-interruptible-openai.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = OpenAISTTService(
@@ -90,6 +91,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -97,14 +99,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -112,7 +114,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07h-interruptible-openpipe.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -94,6 +95,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -101,14 +103,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -116,7 +118,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07i-interruptible-xtts.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -92,6 +93,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -99,14 +101,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -114,7 +116,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07j-interruptible-gladia.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -50,11 +51,12 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = GladiaSTTService(
         api_key=os.getenv("GLADIA_API_KEY", ""),
+        region=os.getenv("GLADIA_REGION"),
         params=GladiaInputParams(
             language_config=LanguageConfig(
                 languages=[Language.EN],
@@ -97,6 +99,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -104,21 +107,21 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
     await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07k-interruptible-lmnt.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -85,6 +86,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -92,14 +94,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -107,7 +109,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07l-interruptible-groq.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"))
@@ -90,6 +91,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -97,14 +99,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -112,7 +114,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07m-interruptible-aws.py

@@ -9,6 +9,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -46,7 +47,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = AWSTranscribeSTTService()
@@ -91,6 +92,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -98,14 +100,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "user", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -113,7 +115,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07n-interruptible-gemini.py

@@ -0,0 +1,164 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""
+A conversational AI bot using Gemini for both LLM and TTS.
+
+This example demonstrates how to use Gemini's TTS capabilities with the new
+GeminiTTSService, which uses Gemini's TTS-specific models instead of Google Cloud TTS.
+
+Features showcased:
+- Gemini LLM for conversation
+- Gemini TTS with natural voice control
+- Support for different voice personalities
+- Style and tone control through natural language prompts
+
+Run with:
+    python examples/foundational/gemini-tts.py
+
+Make sure to set your environment variables:
+    export GOOGLE_API_KEY=your_api_key_here
+"""
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.google.llm import GoogleLLMService
+from pipecat.services.google.stt import GoogleSTTService
+from pipecat.services.google.tts import GeminiTTSService
+from pipecat.transcriptions.language import Language
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot with Gemini TTS")
+
+    stt = GoogleSTTService(
+        params=GoogleSTTService.InputParams(languages=Language.EN_US),
+        credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
+    )
+
+    tts = GeminiTTSService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        model="gemini-2.5-flash-preview-tts",  # TTS-specific model
+        voice_id="Charon",
+        params=GeminiTTSService.InputParams(language=Language.EN_US),
+    )
+
+    llm = GoogleLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        model="gemini-2.5-flash",
+    )
+
+    # System message that instructs the AI on how to speak
+    messages = [
+        {
+            "role": "system",
+            "content": """You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
+
+            IMPORTANT: Since you're using Gemini TTS which supports natural voice control, you can include speaking instructions in your responses. For example:
+            - "Say cheerfully: Welcome to our conversation!"
+            - "Read this in a calm, professional tone: Here are the details you requested."
+            - "Speak in an excited whisper: I have some great news to share!"
+            - "Say slowly and clearly: Let me explain this step by step."
+
+            Feel free to use natural language instructions to control your voice style, tone, pace, and emotion. The TTS system will interpret these instructions and adjust the speech accordingly.
+
+            Your output will be converted to audio, so avoid special characters in your answers. Respond to what the user said in a creative and helpful way.""",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,  # STT
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # Gemini TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation with a styled introduction
+        messages.append(
+            {
+                "role": "system",
+                "content": "Say cheerfully and warmly: Hello! I'm your AI assistant powered by Gemini's new TTS technology. I can speak with different voices, tones, and styles. How can I help you today?",
+            }
+        )
+        await task.queue_frames([LLMRunFrame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+    await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/07n-interruptible-google.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = GoogleSTTService(
@@ -98,6 +99,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -105,14 +107,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -120,7 +122,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07o-interruptible-assemblyai.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = AssemblyAISTTService(
@@ -91,6 +92,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -98,14 +100,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -113,7 +115,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07p-interruptible-krisp.py

@@ -12,6 +12,7 @@ from loguru import logger
 
 from pipecat.audio.filters.krisp_filter import KrispFilter
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -52,7 +53,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -89,6 +90,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -96,14 +98,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -111,7 +113,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07q-interruptible-rime-http.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -50,7 +51,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -94,6 +95,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -101,14 +103,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -116,7 +118,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07q-interruptible-rime.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,6 +89,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -95,14 +97,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -110,7 +112,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07r-interruptible-riva-nim.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = RivaSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
@@ -85,6 +86,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -92,14 +94,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -107,7 +109,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07s-interruptible-google-audio-in.py

@@ -18,6 +18,7 @@ from pipecat.frames.frames import (
     InputAudioRawFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
+    LLMRunFrame,
     StartInterruptionFrame,
     TextFrame,
     TranscriptionFrame,
@@ -213,7 +214,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     llm = GoogleLLMService(
@@ -266,6 +267,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -273,14 +275,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -288,7 +290,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07t-interruptible-fish.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -89,6 +90,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -96,14 +98,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -111,7 +113,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07u-interruptible-ultravox.py

@@ -59,7 +59,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = CartesiaTTSService(
@@ -82,6 +82,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -93,7 +94,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -101,7 +102,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07v-interruptible-neuphonic-http.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -50,7 +51,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -93,6 +94,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -100,14 +102,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -115,7 +117,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07v-interruptible-neuphonic.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -48,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,6 +89,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -95,14 +97,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -110,7 +112,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07w-interruptible-fal.py

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,7 +50,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = FalSTTService(
@@ -91,6 +92,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -98,14 +100,14 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -113,7 +115,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07x-interruptible-local.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -78,7 +79,7 @@ async def main():
     )
 
     messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-    await task.queue_frames([context_aggregator.user().get_context_frame()])
+    await task.queue_frames([LLMRunFrame()])
 
     runner = PipelineRunner()
 

examples/foundational/07y-interruptible-minimax.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -51,7 +52,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     # Create an HTTP session
@@ -95,6 +96,7 @@ async def run_bot(transport: BaseTransport):
                 enable_metrics=True,
                 enable_usage_metrics=True,
             ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
 
         @transport.event_handler("on_client_connected")
@@ -102,14 +104,14 @@ async def run_bot(transport: BaseTransport):
             logger.info(f"Client connected")
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
             await task.cancel()
 
-        runner = PipelineRunner(handle_sigint=False)
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
         await runner.run(task)
 
@@ -117,7 +119,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/07z-interruptible-sarvam-http.py

@@ -0,0 +1,126 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+import os
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.sarvam.tts import SarvamHttpTTSService
+from pipecat.transcriptions.language import Language
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+        tts = SarvamHttpTTSService(
+            api_key=os.getenv("SARVAM_API_KEY"),
+            aiohttp_session=session,
+            params=SarvamHttpTTSService.InputParams(language=Language.EN),
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
+
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            logger.info(f"Client connected")
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_client_disconnected")
+        async def on_client_disconnected(transport, client):
+            logger.info(f"Client disconnected")
+            await task.cancel()
+
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+        await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/07z-interruptible-sarvam.py

@@ -5,6 +5,7 @@
 #
 
 
+import asyncio
 import os
 
 import aiohttp
@@ -12,6 +13,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -21,7 +23,6 @@ from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.sarvam.tts import SarvamTTSService
-from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
 from pipecat.transports.services.daily import DailyParams
@@ -51,72 +52,73 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
-    # Create an HTTP session
-    async with aiohttp.ClientSession() as session:
-        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-        tts = SarvamTTSService(
-            api_key=os.getenv("SARVAM_API_KEY"),
-            aiohttp_session=session,
-            params=SarvamTTSService.InputParams(language=Language.EN),
-        )
+    tts = SarvamTTSService(
+        api_key=os.getenv("SARVAM_API_KEY"),
+        model="bulbul:v2",
+        voice_id="manisha",
+    )
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
-        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
 
-        messages = [
-            {
-                "role": "system",
-                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-            },
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
         ]
+    )
 
-        context = OpenAILLMContext(messages)
-        context_aggregator = llm.create_context_aggregator(context)
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
 
-        pipeline = Pipeline(
-            [
-                transport.input(),  # Transport user input
-                stt,
-                context_aggregator.user(),  # User responses
-                llm,  # LLM
-                tts,  # TTS
-                transport.output(),  # Transport bot output
-                context_aggregator.assistant(),  # Assistant spoken responses
-            ]
-        )
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMRunFrame()])
 
-        task = PipelineTask(
-            pipeline,
-            params=PipelineParams(
-                enable_metrics=True,
-                enable_usage_metrics=True,
-            ),
-        )
+        # Optionally, you can wait for 30 seconds and then change the voice.
+        # await asyncio.sleep(30)
+        # await task.queue_frame(TTSUpdateSettingsFrame(settings={"voice": "anushka"}))
 
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            logger.info(f"Client connected")
-            # Kick off the conversation.
-            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
 
-        @transport.event_handler("on_client_disconnected")
-        async def on_client_disconnected(transport, client):
-            logger.info(f"Client disconnected")
-            await task.cancel()
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-        runner = PipelineRunner(handle_sigint=False)
-
-        await runner.run(task)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/08-bots-arguing.py

@@ -6,9 +6,13 @@ from typing import Tuple
 import aiohttp
 from dotenv import load_dotenv
 
-from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
+from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.processors.aggregators import SentenceAggregator
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.runner.daily import configure
 from pipecat.services.azure import AzureLLMService, AzureTTSService
 from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -79,7 +83,7 @@ async def main():
             sentence_aggregator = SentenceAggregator()
             pipeline = Pipeline([llm, sentence_aggregator, tts1], source_queue, sink_queue)
 
-            await source_queue.put(LLMMessagesFrame(messages))
+            await source_queue.put(OpenAILLMContextFrame(OpenAILLMContext(messages)))
             await source_queue.put(EndFrame())
             await pipeline.run_pipeline()
 

examples/foundational/09-mirror.py

@@ -72,7 +72,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     pipeline = Pipeline([transport.input(), MirrorProcessor(), transport.output()])
@@ -80,6 +80,7 @@ async def run_bot(transport: BaseTransport):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -91,7 +92,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -99,7 +100,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/09a-local-mirror.py

@@ -75,7 +75,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tk_root = tk.Tk()
@@ -97,6 +97,7 @@ async def run_bot(transport: BaseTransport):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     async def run_tk():
@@ -115,7 +116,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await asyncio.gather(runner.run(task), run_tk())
 
@@ -123,7 +124,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/10-wake-phrase.py

@@ -49,7 +49,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -92,6 +92,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -105,7 +106,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -113,7 +114,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/11-sound-effects.py

@@ -101,7 +101,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -143,7 +143,10 @@ async def run_bot(transport: BaseTransport):
         ]
     )
 
-    task = PipelineTask(pipeline)
+    task = PipelineTask(
+        pipeline,
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
@@ -157,7 +160,7 @@ async def run_bot(transport: BaseTransport):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -165,7 +168,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/12-describe-video.py

@@ -11,7 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -70,7 +70,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     user_response = UserResponseAggregator()
@@ -103,7 +103,10 @@ async def run_bot(transport: BaseTransport):
         ]
     )
 
-    task = PipelineTask(pipeline)
+    task = PipelineTask(
+        pipeline,
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
@@ -116,14 +119,14 @@ async def run_bot(transport: BaseTransport):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await tts.say("Hi there! Feel free to ask me what I see.")
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -131,7 +134,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/12a-describe-video-gemini-flash.py

@@ -11,7 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -70,7 +70,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     user_response = UserResponseAggregator()
@@ -109,6 +109,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -122,14 +123,14 @@ async def run_bot(transport: BaseTransport):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await tts.say("Hi there! Feel free to ask me what I see.")
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -137,7 +138,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":

examples/foundational/12b-describe-video-gpt-4o.py

@@ -11,7 +11,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -70,7 +70,7 @@ transport_params = {
 }
 
 
-async def run_bot(transport: BaseTransport):
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     user_response = UserResponseAggregator()
@@ -109,6 +109,7 @@ async def run_bot(transport: BaseTransport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
 
     @transport.event_handler("on_client_connected")
@@ -122,14 +123,14 @@ async def run_bot(transport: BaseTransport):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await tts.say("Hi there! Feel free to ask me what I see.")
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
         await task.cancel()
 
-    runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
     await runner.run(task)
 
@@ -137,7 +138,7 @@ async def run_bot(transport: BaseTransport):
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
     transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":